• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.340-350
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• 2022

The big data term refers to the great volume of data and complicated data structure with difficulties in collecting, storing, processing, and analyzing these data. Big data analytics refers to the operation of disclosing hidden patterns through big data. This information and data set cloud to be useful and provide advanced services. However, analyzing and processing this information could cause revealing and disclosing some sensitive and personal information when the information is contained in applications that are correlated to users such as location-based services, but concerns are diminished if the applications are correlated to general information such as scientific results. In this work, a survey has been done over security and privacy challenges and approaches in big data. The challenges included here are in each of the following areas: privacy, access control, encryption, and authentication in big data. Likewise, the approaches presented here are privacy-preserving approaches in big data, access control approaches in big data, encryption approaches in big data, and authentication approaches in big data.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.27-32
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• 2022

The fifth generation (5G) mobile communication technology is designed to meet all communication needs. Heterogeneous networks (HetNets) are a new emerging network structure. HetNets have greater potential for radio resource reuse and better service quality than homogeneous networks since they can evolve small cells into macrocells. Effective resource allocation techniques reduce inter-user interference while optimizing the utilization of limited spectrum resources in HetNets. This article discusses resource allocation in 5G HetNets. This paper explains HetNets and how they work. Typical cell types in HetNets are summarized. Also, HetNets models are explained in the third section. The fourth component addresses radio resource control and mobility management. Moreover, future study in this subject may benefit from this article's significant insights on how HetNets function.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.223-228
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• 2022

Femtocells are being incorporated into heterogeneous networks in order to increase the network capacity. However, intensive deployment of femtocells results in undesired interference, which lowers the system's performance. Controlling the femtocell transmission power is one of of the aspects that can be addressed in order to mitigate the negative effects of the interference. It may also be utilized to facilitate the auto-configuration of the network's conductance, if necessary. This paper proposes the use of an auto-configuration technique for transmission power. The suggested technique is based on the transmission power of macrocells and the coverage provided by femtocells. The simulation findings show that the network's capacity has increased, and the amount of interference has decreased.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.394-400
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• 2022

The radio resources available in a wireless network system are limited. Therefor, job of managing resources is not easy task. Because the resources are shared among the UEs that are connected, the process of assigning resources must be carefully controlled. The packet scheduler in an LTE network is in charge of allocating resources to the user equipment (UE). Femtocells networks are being considered as a promising solution for poor channel performance for mulitple environments. The implementation of femtocells into a macrocell (traditional base station) would boost the capacities of the cellular network. To increase femtocells network capacity, a reliable Packet Scheduler mechanism should be implemented. The Packet Scheduler technique is introduced in this paper to maximize capacity of the network while maintaining fairness among UEs. The proposed solution operates in a manner consistent with this principle. An analysis of the proposed scheme's performance is conducted using a computer simulation. The results reveal that it outperforms the well-known PF scheduler in terms of cell throughput and average throughput of UEs.

• International Journal of Computer Science & Network Security
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• 제21권12호
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• pp.149-156
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• 2021

This study intended to test the structure of the latent factor of an effectiveness scale and the stability of invariance across groups of students' classifications (gender and levels of education). In the large, non-clinical sample (850), students completed the effectiveness scale. The (CFA) confirmatory factor analysis was used to investigate the factor-structure of the measure, and multiple-group confirmatory factor analysis (MGCFA) model was used to test the stability of invariance across groups of students' classifications. The findings of the CFA indicated support for the original four-factor model. Additional analyses of the MGCFA method support the measurement (configural, metric and strong) invariant and practical invariant components of this model. There was an invariant across gender. There was partially invariant across groups of levels of education. The scale exists in groups of levels of education assess the same concepts of, excluding Items 15 and 10. Given that this study is the first investigation for the structure of the effectiveness scale.

• International Journal of Computer Science & Network Security
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• 제22권8호
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• pp.187-196
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• 2022

The law gives the Ministry of Commerce the power of monitoring, oversight, and accountability for corporations in general. However, Article 219 of the Companies Law has made oversight of listed companies within the jurisdiction of the Capital Market Authority, but this exception, in the author's opinion, is not clear because the law obligated the Ministry of Commerce to monitor and account for joint-stock companies, whether they were listed or not included in some cases.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.17-24
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• 2022

Hierarchical clustering methods have been proposed for more than sixty years and yet are used in various disciplines for relation observation and clustering purposes. In 1965, divisive hierarchical methods were proposed in biological sciences and have been used in various disciplines such as, and anthropology, ecology. Furthermore, recently hierarchical methods are being deployed in economy and energy studies. Unlike most clustering algorithms that require the number of clusters to be specified by the user, hierarchical clustering is well suited for situations where the number of clusters is unknown. This paper presents an overview of the hierarchical clustering algorithm. The dissimilarity measurements that can be utilized in hierarchical clustering algorithms are discussed. Further, the paper highlights the various and recent disciplines where the hierarchical clustering algorithms are employed.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.1-4
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• 2022

The growth in global population and industrialization has led to an increasing demand for electricity. Accordingly, the electricity providers need to increase the electricity generation. Due to the economical and environmental concerns associated with the generation of electricity from fossil fuels. Alternative power recourses that can potentially mitigate the economical and environmental are of interest. Renewable energy resources are promising recourses that can participate in producing power. Among renewable power resources, solar energy is an abundant resource and is currently a field of research interest. Photovoltaic solar power is a promising renewable energy resource. The power output of PV systems is mainly affected by the solar irradiation and ambient temperature. this paper investigates the utilization of machine learning unsupervised neural network techniques that potentially improves the reliability of PV solar power systems during integration into the electrical grid.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.5-10
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• 2022

Photovoltaic systems provide a reliable green energy solution. The sustainability and low-maintenance of Photovoltaic systems motivate the integration of Photovoltaic systems into the electrical grid and further contribute to a greener environment, as the system does not cause any pollution or emissions. Developing methodologies based on machine learning techniques to assist in reducing the burden of studies related to integrating Photovoltaic systems into the electric grid are of interest. This research aims to develop a methodology based on a unsupervised machine learning algorithm that can reduce the burden of extensive studies and simulations related to the integration of Photovoltaic systems into the electrical grid.

• International Journal of Computer Science & Network Security
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• 제22권5호
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• pp.303-311
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• 2022

Through our study, bill of exchange is defined as a written document that contains an order from the drawer directed to the drawee during which the predetermined amount must be paid within a certain time period or on sight. The research begins with an examination of how it was founded, the parties involved, and the organizer's formal conditions. Then, it discusses how to negotiate a bill of exchange through endorsement along with the different types of endorsement and its ramifications. The research concludes by elucidating the bill of exchange impact on the business community, since it decreases commercial conflicts and enables merchants to benefit from, circulate, and recycle their debts without being damaged by debts collection delays.